Welcome to Thoughts on AI, a new blog series focused on issues and advances in artificial intelligence. We’ll cover the technologies and people shaping the future AI. First up: avoiding bias built into intelligence and analytics.
Moving data often impacts system performance, so how do you move large volumes of data safely and securely? The importance of data movement is even more critical when you consider moving data from ground to Cloud. Joe Bostian, z Systems Data Science Architect, IBM Analytics, and Mythili
Augmented reality (AR) and augmented intelligence systems such as Watson are breaking data outside the confines of a two-dimensional monitor and putting them into a three-dimensional visualization format. Big Data and Analytics Hub spoke with IBM AR designer Ben Resnick about what’s next for
From machine learning to blockchain to artificial intelligence, data is dominating the conversation in the tech industry. In the first episode of Data Decoded, William McKnight, CEO of McKnight Consulting, and Yves Mulkers, founder of 7wData and a data/business intelligence architect, discuss the
In this week's episode of Making Data Simple, Al Martin and Adam Storm, IBM senior technical staff member and master inventor, next-generation HTAP architect, sit down to talk about fast data. Adam also covers the pros and cons of different information architectures and the software you can use to
In this episode of the Making Data Simple Podcast, Seth Dobrin, vice president and chief data officer for IBM Analytics, and Al Martin continue their conversation about data in 2018. Find out the six steps to make your enterprise data driven, how machine learning and AI will impact your business
What's next in the world of data and analytics in 2018? In part one of Al Martin's discussion with Seth Dobrin, Vice President and Chief Data Officer for IBM Analytics, explore the strategies and people your company needs to disrupt and succeed in the year ahead. Do you or your team members need
If you work in the field of sales commissions, you’re likely aware of ASC 606, the five-step revenue recognition model and timelines. The basic premise on which both ASC 606 and IFRS 15 have been formulated is that an organization can recognize revenue from a customer contract only when the
Organizations everywhere, from massive governments to the smallest start-ups, are in a race for the best-possible data expertise and tools. To help your team understand the data science journey, IBM created the Data Science for All webcast.
Machine learning concerns in Silicon Valley tend to be different from those elsewhere in the U.S. — and outside of the U.S. So, here are five tips for those hearing about machine learning efforts in Silicon Valley, but who work elsewhere. These suggestions consider where machine learning and data
What is driving change in the world of data? In his keynote from the Big Data Summit KC 2017, our Making Data Simple podcast host and IBM Analytics VP Al Martin addresses disruption, the data maturity model and the five areas business must get right to succeed in the era of cognitive computing.
If you’re holding an event for the very first time, what helps you gauge its success? At IBM Analytics University, we turned to social media analytics. Here’s a summary of what we learned from the experts and from Watson Analytics for Social Media.
IBM Analytics is coming to Berlin and New Orleans this October. Here are five traits that make the conference unique. Can't make it? Join the Facebook livestream on October 10 or watch the replay to hear the opening session keynotes from Joel Shapiro and Marc Altshuller.